Triple
T4773342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duquesne Incline |
E105983
|
entity |
| Predicate | hasOperatorRoom |
P5521
|
FINISHED |
| Object | upper station |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: upper station | Statement: [Duquesne Incline, hasOperatorRoom, upper station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOperatorRoom Context triple: [Duquesne Incline, hasOperatorRoom, upper station]
-
A.
hasRoom
chosen
Indicates that an entity possesses, contains, or is associated with a specific room.
-
B.
operatesFacility
Indicates that an entity is responsible for running, managing, or controlling the operations of a particular facility.
-
C.
hasParkOperator
Indicates that a park is operated or managed by a specific organization or individual.
-
D.
operatorCab
Indicates that a person or organization serves as the operating company or carrier responsible for running a specific cab or taxi service.
-
E.
hasMapRoom
Indicates that an entity includes or provides access to a dedicated room or space used for displaying or working with maps.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6560b3448190a0debbd8da29d986 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.